I am using OutFLANK2 to analyze a set of ~44,000 SNPs from a species across Latin America. They are from different countries with high geographic distance , but still classified as the same species. Some of the data was NA, but i change it for 9 as indicated, so the initial snap matrix was ok.
I am following the vignette, but preliminary results before running the program indicate high FST values, with some being 1. From the distribution, it seems that they do not follow a chi-squared distribution due to high heterogeneity. Do you have any insights on what I could do or why the data is showing this characteristic? I tried continuing with the program, but it was not able to identify any outliers.
Hi Katie .
I am using OutFLANK2 to analyze a set of ~44,000 SNPs from a species across Latin America. They are from different countries with high geographic distance , but still classified as the same species. Some of the data was NA, but i change it for 9 as indicated, so the initial snap matrix was ok.
I am following the vignette, but preliminary results before running the program indicate high FST values, with some being 1. From the distribution, it seems that they do not follow a chi-squared distribution due to high heterogeneity. Do you have any insights on what I could do or why the data is showing this characteristic? I tried continuing with the program, but it was not able to identify any outliers.
Thanks!